Terrence Sejnowski's goal is to discover the principles linking brain mechanisms and behavior. His laboratory uses both experimental and modeling techniques to study the biophysical properties of synapses and neurons and the population dynamics of large networks of neurons.
Global Epigenomic Reconfiguration During Mammalian Brain Development
Several lines of evidence point to a key role for dynamic epigenetic changes during brain development, maturation, and learning. DNA methylation (mC) is a stable covalent modification that persists in post-mitotic cells throughout their lifetime, defining their cellular identity. However, the methylation status at each of the ~1 billion cytosines in the genome is potentially an information-rich and fl exible substrate for epigenetic modification that can be altered by cellular activity. Indeed, changes in DNA methylation have been implicated in learning and memory, as well as in age-related cognitive decline. However, little is known about the cell type–specific patterning of DNA methylation and its dynamics during mammalian brain development.
We have collaborated with the Ecker lab at Salk to seuqence the methylome of neurons and glia cells from mice and humans. Widespread methylome reconfiguration occurs during fetal to young adult development, coincident with synaptogenesis. During this period, highly conserved non-CG methylation (mCH) accumulates in neurons, but not glia, to become the dominant form of methylation in the human neuronal genome. Moreover, we found an mCH signature that identifies genes escaping X-chromosome inactivation. Last, whole-genome single-base resolution 5-hydroxymethylcytosine (hmC) maps revealed that hmC marks fetal brain cell genomes at putative regulatory regions that are CG-demethylated and activated in the adult brain and that CG demethylation at these hmC-poised loci depends on Tet2 activity.
This project has produced a rich data set that we continue to analyze. We are particulalry interested in looking for specific genes that are methylated during development that may be involved in synaptogenesis. We have also studied the neural methylome of the preforntoal cortex in a mouse model of schizophrenia.
For background see:
Computing with Spikes
In recordings from the LGN of the cat in response to an irregularly fluctuating whole-field stimulus, neurons fired spikes at highly reliable spike times, with millisecond precision, across trials, across neurons, and across cats. Although this stimulus is unnatural, the results of the experiment show that neurons in the visual system can respond with great timing precision. Synchronous spikes occur in neighboring ganglion cells when objects are moving across the visual field.
We have developed a detailed biophysical model of the spiny stellate neurons in the primary visual cortex. The convergence of synchronous LGN inputs onto spiny stellate neurons can drive these neurons reliably, even though only 95 percent of the synapses on these neurons are from other cortical neurons. We estimated that the optimal number of synchronously firing inputs needed for reliable transmission of information was about 4 to 6 LGN fibers, each of which makes 2 to 10 synapses on the spiny stellate cell. The receptive fields of cortical neurons are elongated, compared with ganglion cells, whose receptive fields are circular. We will be using spike trains recorded simultaneously from 100 ganglion cells in response to movies. These recordings will be used as inputs to Hodgkin-Huxley models of cortical neurons that receive converging inputs from this array of ganglion cells relayed through the LGN. The goal is to determine how the elongated receptive fields are created in the cortex and the extent to which convergence of synchronous spikes from several ganglion cells may be responsible for synthesis of feature selectivity in the cortex. For more background information about this project see: http://papers.cnl.salk.edu/?SearchText=delbruck